“Everything should be made as simple as possible, but not simpler” -Albert Einstein
Applicant Tracking Systems, or ATS, are the tool of choice for HR departments to – at least in theory – streamline their hiring process and gather valuable data across the different stages of their application funnel.
Gone are the days of paper resumes. Nowadays, applicants resort to the web to apply for jobs, submitting their information digitally. This is the information that hiring managers receive through their ATS software.
However, ATS solutions are not without their share of problems, especially for job applicants. These problems may keep job seekers from even applying in the first place, killing the funnel performance right at the start.
This post covers:
- The math behind recruitment success and how to optimize it
- How to analyze an application funnel, optimizing its flow
- How to implement quick application flows
Recruitment Success: A Simple Calculus
Recruitment success can be modeled mathematically.
When approached on a “per hire” basis, recruitment success can be expressed as:
Therefore, in order to optimize recruitment success, recruiters need to go through every variable of the above equation, optimizing each of them.
These variables can be broken down into the following components:
Top of Funnel Volume
The Top of the Funnel (ToFu) is where applicants enter the pipeline and the sourcing itself begins. Here, employment branding and recruitment marketing play a role in drawing in visitors to the different company pages and job postings. A well implemented messaging and branding strategy should make companies enticing enough for visitors to turn into applicants.
In order to optimize ToFu volumes, it is important to get as many applicants as possible. This sourcing effort happens across various digital channels or touchpoints:
These are all channels where prospective applicants interact with their digital devices and where employers can reach them through the different types of available job ads. These include programmatic ads, which allow employers to target and reach the most relevant job seekers.
An optimized ToFu, i.e., one that leverages the benefits of programmatic recruitment ads, will get many more qualified job seekers clicking on those job postings, thus entering into the application funnel.
As we previously defined in our Introduction to Recruitment Analytics, the cost per applicant (CPA) metric refers to the:
“cost of a job seeker performing some sort of action within the application funnel (e.g. contact info submit; background check submit; etc.)”
The CPA begins counting once the job seeker completes the first step of an application flow. For example, a 3-step application funnel could include the following stages:
- Contact information
- Personal information
- Background check
Once the job seeker submits his or her contact information, the CPA starts counting, with each subsequent step adding up to the total cost.
When taken into account effectively, cost per applicant might provide a clearer picture of the efficacy of recruitment budgets.
Many factors can negatively affect conversion rates. Poor usability creates friction points for job seekers, who may then decide against applying for a particular offer.
A common obstacle is the number of steps required to fill out online application forms. Many ATS implement multi-page flows that, in some cases, do not even feature saving capabilities – if the applicant cannot complete the form right on the spot, he or she cannot return to it later, therefore dropping off entirely.
This candidate experience stage of the funnel requires an optimal user experience (UX) in order to maximize conversion rates – that is, turning visitors into actual applicants and then interviewees.
This key metric refers to the total internal and external recruitment costs divided by the total number of hires within a given time period. As interviewees become hires, employers need to constantly check this number, as it is indicative of the hiring process economics and recruitment success.
Quality of Hire
Optimal performance levels vary widely, not only between companies but also between positions in the same company. However, even though this metric is business-specific, the overall concept basically refers to the value the new hire contributes after the onboarding process is done.
Times to reach optimal performance also vary, usually taking months to do so, and in this lapse, another crucial factor to take care of is employee churn or the number of employees that leave the company, often times without reaching full productivity. As stated by the website Predictive Analytics Times, employee churn can be massively expensive, thus making it another variable that needs close tracking.
Optimizing Flow: How to Tweak Application Funnels for Optimal Performance
How can companies improve their application flows to optimize recruitment? One way is to actively manage their application funnels.
Every step in the funnel requires careful analysis in order to improve conversion rates, thus maximizing the number of applicants moving from stage to stage and improving the overall candidate experience.
By drawing parallels with the digital marketing conversion funnel, the application funnel can be optimized on a per stage basis as follows:
- Employment branding: How job seekers arrive at the company’s application pages. Here messaging and branding play a crucial role, as these two factors determine how job seekers perceive the company (is it worth it to apply?)
- Sourcing: Here the analysis focuses on the recruiting means – active (job boards, aggregators, social media) and passive (referrals, past candidates still available). A careful review of available sourcing channels and their results is key to optimizing this stage.
- Candidate experience: The candidate experience stage demands an optimal UX effort in order to convert as many applicants as possible
- Candidate selection: Usually, this stage has a high conversion rate – up to 89% according to Jobvite published benchmarks – which means that most offers turn into actual hires. Optimization efforts in this stage are normally focused on choosing the right methods and tools for picking the best possible candidates
- Insights: In this point, conversion has already happened so this stage lets employers know if their optimization efforts are working or not – by means of recruitment analytics and reporting tools
When analyzing application flows for optimization, a recurring problem of most standard ATS-built-in funnels is that these are not optimized for conversions. ToFu rates can be particularly low: only around 11% of job seekers visiting a careers website end up applying.
Conversion rates above that number are actually deemed as indicative of excellent company branding and messaging. Therefore, optimizing this first step by implementing UX design principles guarantees better performance down the funnel by saving on hiring costs and increasing applications.
Common problems include:
- Lack of mobile optimization: No responsive application sites or non-user-friendly mobile apps
- Too complex applications: Job seekers expect online application forms that are easy to use
- Lengthy applications: Forms span across several pages, making the process lengthy and tiresome
- Irrelevant questions: Information requests should focus on necessary information
- Document upload requests: In mobile application forms this is difficult to do and altogether impractical from a user’s perspective
In order to optimize their application flows, the main goal for employers should be reducing complexity, making the application process as easy as possible for applicants. This is the best way to maximize application funnel conversions.
Standard Application vs. Quick Application: How to Improve Application Rates
Nowadays, most popular ATS solutions, unfortunately, lack easy-to-use application flows. Employers might be losing excellent candidates because of poorly designed funnels.
The problem with certain ATS has been captured in this post by Contract Recruiter, where the author lists some of the most common complaints from job seekers regarding popular applicant tracking software Taleo:
- Long application times: Up to 45 minutes for a single job posting
- Applications seemingly getting nowhere: Once completed, employers never reply back
- Unreliable, buggy software: Applications reset to the first page if applicants click the wrong button
- Redundant information requests: Resumes being uploaded twice – once in document format and then again in text forms
The mentioned issues show negative effects of poorly designed application funnels for both job seekers and employers alike. This situation calls for improvements to the process – application flows need to be quick.
Employers can use quick application flows as standalone solutions or A/B tested against existing flows, by driving a percentage of the incoming applicants to a new quick flow. The good news is that most of the above-mentioned problems can be addressed through a quick application page.
Also, people currently spend up to 5 hours a day on their mobile devices, employers cannot afford to overlook the importance of mobile application flows – job seekers will increasingly use their smartphones to apply for open positions and companies need to keep up with this trend by streamlining their flows.
A standard quick application flow can be easily implemented as:
- Page #1: quick contact information capture, focusing on the minimum essential info – name and email, to reach the applicant back in case he or she drops off before finishing the application
- Page #2: additional complimentary personal information to complete the picture
- Page #3: more specific information as required by the position being applied – sometimes including qualification specific information (driver’s license; etc.)
- Page #4: essential professional info to sum up the applicant’s qualifications – here it helps to provide multiple choice options instead of asking the applicant to submit a lengthy ‘free-form’ work history
The data captured on a quick application flow should be just enough to pre-qualify candidates. As a majority of applications happen via mobile phone it is recommended to reduce the required data entry down to 2-3 minutes. Recruiters can get the rest of the candidates’ information via personal interviews, phone or video calls.
The importance of user experience cannot be stressed enough: an optimized application flow requires easy-to-use application pages. The usability principles laid out in this recommended post by Instapages are key to keep job seekers converting into potential hires:
- Consistency: “don’t reinvent the web”, stick to familiar design elements and practices, and ensure job ads match company branding and messaging
- Clarity: make application pages understandable, with descriptive elements
- Concision: application forms should be easy to fill out, for a true quick flow, eliminating superfluous elements
- Credibility: employers should communicate authority and credibility at all times
- Convenience: pages must load as fast as possible and be responsive to all screen sizes
Bottomline: Favor Quick Application Flows Over Standard ATS Flows
A good candidate experience improves application rates and business results. One of the easiest ways of achieving recruitment success is by optimizing your job application flow.
Quick applications are complementary to existing ATS solutions and have serious benefits:
- Increased ‘application complete’ rates which lead to a reduced average CPA (cost-per-applicant)
- As a result, businesses experience a lower average CPH (cost-per-hire)
To get your business started with quick applications, apply the advice above or partner with a programmatic recruitment platform that can set up a custom-built application form for your business.
If you have insights and opinions on this topic please share your thoughts.
Thanks, Team Perengo
Perengo is a programmatic recruitment platform.
High-growth businesses and Fortune 500 companies use Perengo to solve their recruitment challenges at scale. The platform provides tools for operational recruitment automation and strategic business intelligence.